In recent years, the field of computer animation has witnessed the invention of multiple simulation methods that exploit pre-recorded data to improve the performance and/or realism of dynamic deformations. Various methods have been presented concurrently, and they present differences, but also similarities, that have not yet been analyzed or discussed. This course focuses on the application of data-driven methods to three areas of computer animation, namely dynamic deformation of faces, soft volumetric tissue, and cloth. The course describes the particular challenges tackled in a data-driven manner, classifies the various methods, and also shares insights for the application to other settings.

The explosion of data-driven animation methods and the success of their results make this course extremely timely. Up till now, the proposed methods have remained familiar only at the research context, and have not made their way through computer graphics industry. This course aims to fit two main purposes. First, present a common theory and understanding of data-driven methods for dynamic deformations that may inspire the development of novel solutions, and second, bridge the gap with industry, by making data-driven approaches accessible. The course targets an audience consisting of both researchers and programmers in computer animation.